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"Since the early eighties, Ali Suleyman Ustunel has been one of the main contributors to the field of Malliavin calculus. In a workshop held in Paris, June 2010 several prominent researchers gave exciting talks in honor of his 60th birthday. The present volume includes scientific contributions from this workshop. Probability theory is first and foremost aimed at solving real-life problems containing randomness. Markov processes are one of the key tools for modeling that plays a vital part concerning such problems. Contributions on inventory control, mutation-selection in genetics and public-private partnerships illustrate several applications in this volume. Stochastic differential equations, be they partial or ordinary, also play a key role in stochastic modeling. Two of the contributions analyze examples that share a focus on probabilistic tools, namely stochastic analysis and stochastic calculus. Three other papers are devoted more to the theoretical development of these aspects. "

"This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions. Stochastic Processes is ideal for a course aiming to give examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models. It introduces the methods of probability model building and provides the reader with mathematically sound techniques as well as the ability to further study the theory of stochastic processes. Originally published in 1962, this was the first comprehensive survey of stochastic processes requiring only a minimal background in introductory probability theory and mathematical analysis. Stochastic Processes continues to be unique, with many topics and examples still not discussed in other textbooks. As new fields of applications (such as finance and DNA analysis) become important, researchers will continue to find the fundamental and accessible topics explained in this book essential background for their research."

"Research on algorithms and applications of stochastic programming, the study of procedures for decision making under uncertainty over time, has been very active in recent years and deserves to be more widely known. This is the first book devoted to the full scale of applications of stochastic programming and also the first to provide access to publicly available algorithmic systems. The 32 contributed papers in this volume are written by leading stochastic programming specialists and reflect the high level of activity in recent years in research on algorithms and applications. The book introduces the power of stochastic programming to a wider audience and demonstrates the application areas where this approach is superior to other modeling approaches."

"This book develops systematically and rigorously, yet in an expository and lively manner, the evolution of general random processes and their large time properties such as transience, recurrence, and convergence to steady states. The emphasis is on the most important classes of these processes from the viewpoint of theory as well as applications, namely, Markov processes."

"While there are several texts on how to solve and analyze stochastic programs, this is the first text to address basic questions about how to model uncertainty, and how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental issues are. "

"The solution of stochastic equations poses notable technical difficulties that are frequently circumvented by heuristic assumptions at the expense of accuracy and rigor. The main objective of Stochastic Systems is to promoting the development of accurate and efficient methods for solving stochastic equations and to foster interactions between engineers, scientists, and mathematicians. To achieve these objectives Stochastic Systems presents, a clear and brief review of essential concepts on probability theory, random functions, stochastic calculus, Monte Carlo simulation, and functional analysis, probabilistic models for random variables and functions needed to formulate stochastic equations describing realistic problems in engineering and applied sciences, practical methods for quantifying the uncertain parameters in the definition of stochastic equations, solving approximately these equations, and assessing the accuracy of approximate solutions."

"Angkutan umum/bis merupakan salah satu mode angkutan umum yang sangat dibutuhkan oleh sejumlah besar masyarakat terutama golongan menengah ke bawah. Permasalahan pokok yang dihadapi oleh pemakai jasa /user adalah tidak adanya waktu keberangkatan angkutan umum/bis yang tepat, sehingga mempengaruhi waktu perjalanan, waktu tunggu dan sebagainya, Berta cenderung akan mengharapkan jumlah bis yang beroperasi lebih banyak, karena semakin banyak bis yang beroperasi akan semakin cepat waktu keberangkatannya dan semakin kecil waktu tunggunya. Sedangkan permasalahan dari pihak operator/pengelola angkutan umum, akan cenderung untuk membatasi jumlah angkutan umum/bis pada tingkat pelayanan yang paling menguntungkan.Pendekatan model yang digunakan untuk pemecahan masalah adalah dengan melakukan optimasi pada proses penjadualan angkutan umum/bis berdasarkan waktu keberangkatan bis yang optimal dengan proses yang dinamik. Dengan mengetahui waktu keberangkatan bis yang optimal, maka didapat besar probabilitas penumpang yang dapat naik pada bis yang pertama kali datang di suatu pemberhentian, setelah kedatangannya penumpang tersebut di suatu pemberhentian tersebut.Model yang digunakan untuk pemecahan masalah adalah pengembangan model yang dikemukanan oleh Yosef Sheffi dan Morihisa Sugiyama, yang dikembangkan kembali oleh Dr.Ir. Sutanto Soehodho, MEng (1992). Pengembangan model tersebut mencakup metode untuk penjadualan waktu keberangkatan bis pada rute tunggal. Masalah formulasi program matematika dibatasi dengan kapasitas angkutan umum/bis, jumlah pemberhentian/halte dan jumlah armada yang dibutuhkan. Sedangkan tingkat kedatangan penumpang disetiap pemberhentian/halte, probability perpindahan anal tujuan penumpang dan waktu perjalanan armada dari suatu pemberhentian ke pemberhentian lain dibuat secara asumsi data.Sebagai solusinya digunakan prosedur dari "Dynamic Programming. Sehingga didapat optimasi penjadualan berdasarkan permintaan stokastik (Stochastic Demand).Studi kasus dalam pemecahan masalah dipilih Angkutan umum/bis dengan rute tunggal dengan jumlah bis yang optimal didapat sebesar 3 bis. Hasil analisa menunjukan bahwa waktu keberangkatan yang optimal yang didapat dengan menggunakan "Dynamic Programming" adalah sebagai berikut :Untuk bis yang pertama mempunyai selang waktu selama 23 menit dari waktu yang dijadualkan. Sedangkan untuk bis yang kedua mempunyai selang waktu 14 menit dari bis yang pertama dan untuk bis yang ketiga mempunyai selang waktu 23 merit dengan bis yang kedua.Adapun hasil dari Program Dinamik tersebut, maka didapatkan waktu keberangkatan yang menghasilkan harga Probabilitas Kejadian X yang optimal yaitu kejadian dimana penumpang dapat naik pada bis yang pertama kali datang di suatu pemberhentian, setelah kedatangannya penumpang tersebut di suatu pemberhentian tersebut."

"Stochastic Frontier Analysis dikembangkan sebagai model pengukuran efisiensi yang mempunyai metode econometric dan parametric. Data yang digunakan dapat bcrupa cross sectional data atau panel data, semakin banyak data yang tersedia maka pengukuran akan semakin akurat. Stochastic Frontier Analysis telah banyak digunakan dalam pengukuran efisiensi pada berbagai industri.Dalam penelitian dilakukan analisis kinerja pada 12 perusahaan di sektor pertambangan dengan menggunakan balanced panel data periode waktu mulai tahun 2003 sampai dengan tahun 2006. Sektor pertambangan sendiri terbagi dalam empat sub sektor yaitu batu bara, minyak dan gas bumi, logam dan mineral lainnya, dan batu-batuan Penggunaan Stochastic Frontier Analysis diharapkan dapat memberikan estimasi pengukuran efisiensi yang lebih baik, karena tidak menggunakan salah satu perusahaan sebagai benchmark.Dalam karya akhir ini akan diteliti pula pengaruh explanatory variable pada kinerja efisiensi perusahaan. Variabel-variabel tersebut adalah Size, hutang jangka panjang, umur perusahaan, ownership dan sub-sektor pertambangan. Variabel Ownership akan dibagi antara perusahaan milik Pemerintah RI dan perusahaan milik swasta, sedangkan sub-sektor pertambangan akan dibagi menjadi kelompok energi dan non energi.

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Stochastic Frontier Analysis has developed as a model for measuring efficiency of production which has an econometric and parametric method. The model can be used for cross sectional data or panel data. The availability of supporting data can make a better estimation of the technical efficiency. Stochastic Frontier Analysis has been used in many researches in some industries.

In this research, 12 mining companies in Indonesia have been measured. The data used are balanced panel data with the period of 2003 until 2006. The mining sector itself is divided into 4 sub-sector, which are cgal mining, crude petroleum and natural gas production, metal and mineral mining) and land I stone quarrying. The measurement using Stochastic Frontier Analysis is expected to be more adequate than other method, because Stochastic Frontier Analysis does not use one of the company as a benchmark.

In this research, it will also use some explanatory variable that can affect the technical efficiency. These variables are size, risk, age. ownership and mining sub-sector. Ownership variable will be divided into government and private owner. While the mining sub-sector variable will be divided into energy group and non energy group."